Stochastic Control of Hereditary Systems and Applications

  • Mou-Hsiung Chang

Part of the Stochastic Modelling and Applied Probability book series (SMAP, volume 59)

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Pages 79-125
  3. Pages 203-244
  4. Pages 245-292
  5. Pages 293-331
  6. Back Matter
    Pages 393-406

About this book

Introduction

This research monograph develops the Hamilton-Jacobi-Bellman (HJB) theory through dynamic programming principle for a class of optimal control problems for stochastic hereditary differential systems. It is driven by a standard Brownian motion and with a bounded memory or an infinite but fading memory.

The optimal control problems treated in this book include optimal classical control and optimal stopping with a bounded memory and over finite time horizon.

This book can be used as an introduction for researchers and graduate students who have a special interest in learning and entering the research areas in stochastic control theory with memories. Each chapter contains a summary.

Mou-Hsiung Chang is a program manager at the Division of Mathematical Sciences for the U.S. Army Research Office.

Keywords

Applications Brownian motion Chang Control Hereditary Stochastic Stochastic calculus

Editors and affiliations

  • Mou-Hsiung Chang
    • 1
  1. 1.U.S. Army Research OfficeDurhamUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-75816-9
  • Copyright Information Springer New York 2008
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-75805-3
  • Online ISBN 978-0-387-75816-9
  • Series Print ISSN 0172-4568
  • About this book